Book contents
- Frontmatter
- Contents
- Preface
- Introduction
- Chapter 1 Populations and probability
- Chapter 2 Spurious correlation and probability increase
- Chapter 3 Causal interaction and probability increase
- Chapter 4 Causal intermediaries and transitivity
- Chapter 5 Temporal priority, asymmetry, and some comparisons
- Chapter 6 Token-level probabilistic causation
- Appendix 1 Logic
- Appendix 2 Probabilit
- Bibliography
- Index
Chapter 1 - Populations and probability
Published online by Cambridge University Press: 07 October 2009
- Frontmatter
- Contents
- Preface
- Introduction
- Chapter 1 Populations and probability
- Chapter 2 Spurious correlation and probability increase
- Chapter 3 Causal interaction and probability increase
- Chapter 4 Causal intermediaries and transitivity
- Chapter 5 Temporal priority, asymmetry, and some comparisons
- Chapter 6 Token-level probabilistic causation
- Appendix 1 Logic
- Appendix 2 Probabilit
- Bibliography
- Index
Summary
Type-level probabilistic causation is sometimes called “population-level” probabilistic causation and sometimes “property-level” probabilistic causation. And the items that enter into type-level probabilistic causal relations are called “factors,” or “properties,” or “event types.” The basic idea in the theory of type-level probabilistic causation is that causes raise the probabilities of their effects. A factor C is a property-level probabilistic cause of – or a positive causal factor for – a factor E, if the probability of E is higher in the presence of C than it is in the absence of C. And C is causally negative or causally neutral for E if the presence of C lowers or leaves unchanged the probability of JS, respectively. But this basic idea needs several clarifications and qualifications.
In this chapter, I explain the importance of the idea of a population to type-level probabilistic causal connection. I argue that type-level probabilistic causation is a relation among four things: a cause factor, an effect factor, a token population within which the first is some kind of cause of the second, and, finally, a kind (of population) that is associated with the given token population. Subsequent chapters reveal how important relativity to populations is for the versatility of the probabilistic theory and how it renders the theory immune to a number of criticisms that have recently been advanced.
Of course, some kind of clarification of the idea of probability is in order.
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- Information
- Probabilistic Causality , pp. 22 - 55Publisher: Cambridge University PressPrint publication year: 1991